Skip to main content
SpringerLink
Log in

A Design of Adaptive Genetic Algorithm-Based Optimized Power Amplifier for 5G Applications

  • Published:
Circuits, Systems, and Signal Processing Aims and scope Submit manuscript

Abstract

In this paper, a novel adaptive genetic algorithm (AGA) is presented for the optimization goals. The presented AGA is discussed and implemented on a power amplifier (PA), which is designed for 24 GHz and 5G applications and fabricated in a 65-nm CMOS process. The PA is optimized by the AGA for the high power-added efficiency (PAE), i.e., optimum. In the AGA, we aimed to avoid the local optima and slow convergence rate that exist in the conventional genetic algorithm (CGA). In the AGA, we proposed a parameter tuning method to fine-tune the set of PA circuit component values for faster optimization of the PA to have a high PAE. The proposed AGA provides a significant speed in optimization process as compared to the CGA, and the execution time of the AGA is faster than that of the CGA. The proposed AGA is also verified, and its performance is compared with that of the CGA through multiple multidimensional mathematical benchmark functions. The PA performance parameters are measured, and the results showed that the optimized PA achieves a high gain of 29.9 dB. The Psat of PA is measured as 14.21 dBm, and IIP3 is 13.8 dBm. The simulated result shows the optimized PA with the AGA has PAE of 49.7%, while that with the CGA has PAE of 47.5% at 24 GHz. The final measured PAE of AGA’s optimized PA is 47.1%. The chip area of PA is 0.29 mm2.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

Data Availability

This manuscript has no associated data.

References

  1. J.W. Bandler, Q.S. Cheng, S.A. Dakroury, A.S. Mohamed, M.H. Bakr, K. Madsen, J. Sondergaard, Space mapping: the state of the art. IEEE Trans. Microw. Theory Tech. 52(1), 337–361 (2004)

    Article  Google Scholar 

  2. J. Cai, J.B. King, B.M. Merrick, T.J. Brazil, Pad´eapproximation-based behavioral modeling. IEEE Trans. Microw. Theory Tech. 61(12), 4418–4427 (2013)

    Article  Google Scholar 

  3. S. Callender, S. Pellerano, C. Hull, An E-band power amplifier with 26.3% PAE and 24-GHz bandwidth in 22-nm FinFET CMOS. IEEE J. Solid-State Circuits 54(5), 1266–1273 (2019)

    Article  Google Scholar 

  4. A. Chakrabarti, H. Krishnaswamy, High-power high-efficiency class-E-like stacked mmWave PAs in SOI and bulk CMOS: theory and implementation. IEEE Trans. Microw. Theory Tech. 62(8), 1686–1704 (2014)

    Article  Google Scholar 

  5. K. Chen, X. Liu, D. Peroulis, Widely tunable high-efficiency power amplifier with ultra-narrow instantaneous bandwidth. IEEE Trans. Microw. Theory Tech. 60(12), 3787–3797 (2012)

    Article  Google Scholar 

  6. P. Chen, B.M. Merrick, T.J. Brazil, Bayesian optimization for broadband high-efficiency power amplifier designs. IEEE Trans. Microw. Theory Tech. 63(12), 4263–4272 (2015)

    Article  Google Scholar 

  7. P. Chen, J. Xia, B.M. Merrick, T.J. Brazil, Multiobjective Bayesian optimization for active load modulation in a broadband 20-W GaN Doherty power amplifier design. IEEE Trans. Microw. Theory Tech. 65(3), 860–871 (2016)

    Article  Google Scholar 

  8. H. Chung, E. Tam, W.L. Lo, S.Y.R. Hui, An optimized fuzzy logic controller for active power factor corrector using genetic algorithms. in Practical Handbook of Genetic Algorithms—Applications, (2000) pp. 363–390

  9. T.S. Delwar, W.A. Cahyadi, Y.H. Chung, Visible light signal strength optimization using genetic algorithm in non-line-of-sight optical wireless communication. Optics Commun. 426, 511–518 (2018)

    Article  Google Scholar 

  10. T.S. Delwar, A. Siddique, M.R. Biswal, P. Behera, A.N.Z. Rashed, Y. Choi, J.Y. Ryu, A novel dual mode configurable and tunable high-gain, high-efficient CMOS power amplifier for 5G applications. Integration 83, 77–87 (2022)

    Article  Google Scholar 

  11. V. Giammello, E. Ragonese, G. Palmisano, A transformer-coupling current-reuse SiGe HBT power amplifier for 77-GHz automotive radar. IEEE Trans. Microw. Theory Tech. 60(6), 1676–1683 (2012)

    Article  Google Scholar 

  12. E.U. Haq, I. Ahmad, A. Hussain, I.M. Almanjahie, A novel selection approach for genetic algorithms for global optimization of multimodal continuous functions. Comput. Intell. Neurosci. 2019, 1–14 (2019)

    Article  Google Scholar 

  13. S.R. Helmi, J.H. Chen, S. Mohammadi, High-efficiency microwave and mm-wave stacked cell CMOS SOI power amplifiers. IEEE Trans. Microw. Theory Tech. 64(7), 2025–2038 (2016)

    Article  Google Scholar 

  14. S.A. Hosseini, A. Hajipour, H. Tavakoli, Design and optimization of a CMOS power amplifier using innovative fractional-order particle swarm optimization. Appl. Soft Comput. 85, 105831 (2019)

    Article  Google Scholar 

  15. T.H. Jang, K.P. Jung, J.S. Kang, C.W. Byeon, C.S. Park, 120-GHz 8-stage broadband amplifier with quantitative stagger tuning technique. IEEE Trans. Circuits Syst. I Regul. Pap. 67(3), 785–796 (2019)

    Article  Google Scholar 

  16. K. Katayama, K.T. Chen, T. Baba, Particle swarm optimization for comprehensive 24 GHz amplifier design. J. Signal Process. 22(6), 243–250 (2018)

    Article  Google Scholar 

  17. A. Komijani, A. Natarajan, A. Hajimiri, A 24-GHz,+ 14.5- dBm fully integrated power amplifier in 0.18-/spl mu/m CMOS. IEEE J. Solid-State Circuits 40(9), 1901–1908 (2005)

    Article  Google Scholar 

  18. R. Köprü, FSRFT—fast simplified real frequency technique via selective target data approach for broadband double matching. IEEE Trans. Circuits Syst. II Express Briefs 64(2), 141–145 (2016)

    Google Scholar 

  19. L. Kouhalvandi, O. Ceylan, S. Ozoguz, A review on optimization methods for designing RF power amplifiers. in IEEE 11th International Conference on Electrical and Electronics Engineering (ELECO), (2019). pp. 375–378

  20. L. Kouhalvandi, O. Ceylan, S. Ozoguz, Automated deep neural learning-based optimization for high performance high power amplifier designs. IEEE Trans. Circuits Syst. I Regul. Pap. 67(12), 4420–4433 (2020)

    Article  Google Scholar 

  21. S. Koziel, Shape-preserving response prediction for microwave design optimization. IEEE Trans. Microw. Theory Tech. 58(11), 2829–2837 (2010)

    Article  Google Scholar 

  22. J. Lee, S. Hong, A 24–30 GHz 31.7% fractional bandwidth power amplifier with an adaptive capacitance linearizer. IEEE Trans. Circuits Syst. II: Express Briefs 68(4), 1163–1167 (2020)

    Google Scholar 

  23. C. Li, F. You, T. Yao, J. Wang, W. Shi, J. Peng, S. He, Simulated annealing particle swarm optimization for high-efficiency power amplifier design. IEEE Trans. Microw. Theory Tech. 69(5), 2494–2505 (2021)

    Article  Google Scholar 

  24. S. Manjula, D. Selvathi, Optimal design of low power CMOS power amplifier using particle swarm optimization technique. Wirel. Pers. Commun. 82(4), 2275–2289 (2015)

    Article  Google Scholar 

  25. J. Pang, S. He, Z. Dai, C. Huang, J. Peng, F. You, Design of a post-matching asymmetric Doherty power amplifier for broadband applications. IEEE Microwave Wirel. Compon. Lett. 26(1), 52–54 (2015)

    Article  Google Scholar 

  26. J. Park, S. Kang, S. Hong, Design of a Ka-band cascode power amplifier linearized with cold-FET interstage matching network. IEEE Trans. Microw. Theory Tech. 69(2), 1429–1438 (2020)

    Article  Google Scholar 

  27. R. Sapawi, R.K. Pokharel, S.A. Murad, A. Anand, N. Koirala, H. Kanaya, K. Yoshida, Low group delay 3.1–10.6 GHz CMOS power amplifier for UWB applications. IEEE Microw. Wirel. Compon. Lett. 22(1), 41–43 (2011)

    Article  Google Scholar 

  28. F. Wang, H. Wang, A high-power broadband multi-primary DAT-based Doherty power amplifier for mm-wave 5G applications. IEEE J. Solid-State Circuits 56(6), 1668–1681 (2021)

    Article  Google Scholar 

  29. B.S. Yarman, H.J. Carlin, A simplified real frequency technique applied to broad-band multistage microwave amplifiers. IEEE Trans. Microw. Theory Tech. 30(12), 2216–2222 (1982)

    Article  Google Scholar 

  30. J. Zhang, H.S.H. Chung, W.L. Lo, S.Y. Hui, A.M. Wu, Implementation of a decoupled optimization technique for design of switching regulators using genetic algorithms. IEEE Trans. Power Electron. 16(6), 752–763 (2001)

    Article  Google Scholar 

  31. J. Zhang, H. Chung, S. Y. R. Hui, W. L. Lo, A. Wu, Decoupled optimization of power electronics circuits using genetic algorithm. in Practical Handbook of Genetic Algorithms—Applications, (2000). pp.135–166

  32. Q.J. Zhang, K.C. Gupta, V.K. Devabhaktuni, Artificial neural networks for RF and microwave design-from theory to practice. IEEE Trans. Microw. Theory Tech. 51(4), 1339–1350 (2003)

    Article  Google Scholar 

Download references

Acknowledgements

This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2018R1D1A1B09043286).

Author information

Author notes

  1. Tahesin Samira Delwar and Abrar Siddique have contributed equally to this work.

Authors and Affiliations

  1. Department of Intelligence Robot Engineering, Pukyong National University, Busan, Republic of Korea

    Tahesin Samira Delwar, Abrar Siddique, Unal Aras & Jee Youl Ryu

Authors
  1. Tahesin Samira Delwar
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Abrar Siddique
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Unal Aras
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jee Youl Ryu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jee Youl Ryu.

Ethics declarations

Conflict of interest

The authors declare no conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Delwar, T.S., Siddique, A., Aras, U. et al. A Design of Adaptive Genetic Algorithm-Based Optimized Power Amplifier for 5G Applications. Circuits Syst Signal Process 43, 2–21 (2024). https://doi.org/10.1007/s00034-023-02447-7

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00034-023-02447-7

Keywords

Search

Navigation